Shakespeare wrote in Macbeth, “The night has been unruly: where we lay, Our chimneys were blown down . . . . Some say the earth was feverous, and did shake.” Since the dawn of time, weather has played an important role in the wellbeing and prosperity of human society. Normal weather enables the growth of crops, food, and ultimately, wealth. With the arrival of modern society, the adverse influence of weather extremes has been somewhat controlled, yet many business models remain vulnerable to uncooperative weather. For example, beachside sporting events are rained out, tourist destinations lose visitors when hurricanes loom, roadways are damaged by earthquakes, planes fall from the sky during storms, and blizzards create white-out conditions across entire regions.
Every part of the globe falls victim to different types of weather-related events. Baghdad is subject to sandstorms, daylight is extinguished in Australian as locust swarms arrive, Taiwan suffers from Pacific typhoons, and the Midwestern states of the United States have recurring winter snowstorms. In the winter of 2009, 52 inches of snow fell on the greater Chicago area while the average is only 38 inches, straining contractual relationships between snow removal service providers and their clients.
The following disclosure describes a weather risk management system as implemented with respect to one weather condition, i.e., snowstorms and snow removal in the Midwestern states of the United States. However, this disclosure is to be read broadly to encompass any and all weather-related events around the world where the described principles can be applied with equal force by simply changing the different input variables associated with the event.
Precipitation has been one of man's principal preoccupations. In 1550, Nostradamus published a weather forecasting guide before moving onto other, less reliable yet more infamous predictions. Prediction of weather-based events is futile because of the nonlinearity of the equations underlying these systems. In mathematics, a nonlinear system is a system in which time is not linked with the superposition principle, or put more simply, where an output is not proportional to the input. Nonlinear systems cannot be solved using fixed variables. For example, no equation can predict the outcome of the state lottery. Similarly, no equation can predict the weather reliably. Further, weather is believed to follow the so-called “butterfly effect,” where simple changes in one part of the system produce complex effects throughout the remainder. The inherent unpredictability of weather can only be managed, not bested.
Predicting weather is not unlike predicting stock market fluctuations or lottery drawings. While historical averages are useful to understand potential future results, it is impossible to predict weather far in advance, much less predict extraordinary weather events and conditions that occur infrequently in an area and are based on a juxtaposition of many effects. For snow storms or even blizzards to occur (i.e., heavy snowfalls), weather fronts must collide at a junction of warmer air with greater water density and a polar air mass. As these different air masses connect, overall air density equalizes by releasing water vapor to the ground. If surface temperatures are below the freezing point of water, the water vapor falls as snow.
Meteorologists attempt to predict precipitation deposited on the Earth's surface. Precipitation comes in the form of rain, hail, and snow. The depth of a snowfall is often measured using standard rain gauges having a diameter of 4 inches (plastic) or 8 inches (metal) and adjusted to allow for collection inside the cylinder. Antifreeze liquids may be added to melt snow or ice that falls into the gauge. Once a snowfall is finished accumulating, the amount of water is recorded. When a snow measurement is made, various networks exist across the United States and elsewhere, such as CoCoRAHS® or GLOBE®, to record the measurements. For example, Chicago is situated on the warmer side of Lake Michigan. That large body of water creates effects that result in an significant variability in precipitation from one part of the greater Chicago area to the next. For this reason, index points are taken as references from, for example, the National Oceanic and Atmospheric Administration (NOAA) at different collection sites around Chicago, such as the Chicago Botanical Garden, the Chicago O'Hare Airport, the City of Elgin, and the City of Northbrook. Over the last 150 years, the greater Chicago area has received a yearly average of 38 inches of snow.
Today, most climate experts agree that global warming is a real phenomenon. Increasing atmospheric temperatures tend to increase evaporation, increasing the water vapor in the air, which in turn leads to more precipitations. As average global temperatures rise, average global precipitation increases. Precipitation has generally increased over land north of 30 deg N from 1900 through 2005 but has declined over the tropics since the 1970s. Globally, there has been no statistically significant overall trend in precipitation over the past century, although trends have varied widely by region over time. Once again, the nonlinearity of weather makes forecasting impossible. Global warming is also believed to increase the risk of variability of precipitation, resulting in years with greater than average snowfalls and years with far below average snowfalls. This phenomenon is often called “weather extremes.” Therefore, risk associated with extreme weather conditions is predicted to increase over the coming decades, and solutions and systems to reduce risk associated with these conditions are needed.
Municipalities and other entities, such as shopping mall owners, have large surface areas that require snow removal after snow storms. Snow must be removed quickly, often overnight, so that life and commerce may continue with minimal interruption. Rapid response time requires numerous personnel and a large fleet of snow removal equipment. It is often not viable for municipalities or other entities to incur the cost of ownership of equipment and associated storage and personnel fees to manage infrequent snowfalls. One solution is to contract with a snow removal service provider operating across a larger area. For example, a snow removal corporation may operate in the greater Chicago area and service a plurality of clients at different locations within the area. These service providers may diversify into summer and winter services and cover wide areas to maintain the availability of personnel and equipment.
Municipalities, like other entities, must budget for snow removal costs. Municipalities may elect to sign a per event contract with a snow removal service provider. Under such a contract, each time a snowfalls occurs, the service provider agrees to perform the service for a fixed price. In anticipation of low precipitation years where clients will not require the service but the service provider will nevertheless have to pay fixed costs, the per event price offered takes into consideration and spreads fixed costs. In years of high precipitation, municipalities may end up overpaying for fixed costs that have already been factored into the first few event calls for the year. Further, as the season unfolds, service providers may be overrun with demand in times of exceptional snowfall and incur additional costs such as, for example, overtime pay and extraordinary vehicle maintenance.
Municipalities may strong-arm service providers into signing a fix priced contract for a full season of service. This solution is problematic on many levels for both parties. When precipitation is at a minimum, the municipality may be criticized by taxpayers for contracting and paying for a service it does not use, whereas when precipitations far exceed averages, the financial strain placed on the service provider may result in a failure to perform or other unacceptable outcomes such a bankruptcy. Therefore, what is needed is a system that can be implemented as a layer between the service provider and the client as an alternative to per event or fixed price contracts.
Financial derivatives are financial instruments derived from some form of asset, index, event, value, or condition known as the underlying condition. Rather than trade or exchange the underlying condition itself, derivatives traders enter into agreements to exchange cash or assets over time based on the underlying condition. For example, options contracts are an agreement between two parties, such as between the holder of a stock and a prospective buyer of a stock, to exchange the underlying stock at a future date for a fixed price if a strike price is met or exceeded. The derivative is sold at a premium. At a strike price, i.e., a price upon which money is due based on a realized condition, a payout is made in incremental value based on the underlying condition. In the case of a weather derivative such as a snow precipitation derivative at a location, the strike price can be a fixed quantity of snow, or an expected nominal snow precipitation at the location. The option is then paid out at a payout calculated from a set tick price multiplied by the number of units such as inchs of snow above the strike price or possibly the yearly nominal estimate.
Hedging is a technique to reduce risk using derivatives. For example, a farmer may sign a futures contract to exchange for a specific amount of cash a specified amount of wheat in the future. For the farmer, the uncertainty of the sale price is removed and the miller will have a known availability of wheat. Also, by fixing the price, the farmer is assured a minimum price independent of momentary market conditions, and the miller is also assured the same price.
There are many types of derivatives, including over-the-counter (OTC) derivatives, exchange-traded derivatives (ETD) directed at futures contracts, options contracts, and swaps contracts. U.S. patent application Ser. No. 12/221,935 describes a system for trading derivatives based on natural peril events. This system allows users to bet on different natural events such as snowstorms or hurricanes. Based on the probability of occurrence of an event at any moment in time, shares of a fund are purchased that have a payback in proportion with the assumed risk. In this scenario, a municipality faced with a low probability of being hit with the unusually high snow removal fees associated with a blizzard may hedge against itself by purchasing shares of this derivative. Assuming, for example, a probability of 5% of occurrence and a payback of 15 to 1, a municipality wanting to cover costs of $1 million may invest $66,666 dollars and will collect the needed sum if the blizzard hits. The problem is that a municipality is then engaged in gambling, essentially betting against itself, and 19 times out of 20, losing the invested sum. The solution described in this reference is not well adapted to managing financial risks associated with extreme weather events.
U.S. patent application Ser. No. 11/775,883 describes a system where a service, such as a help line for information technology, must be used and billed “on-demand” while actual usage volumes are unknown. A service provider is then used as an intermediary between an end user of the service and the service provider. The payment of a fee by the user is split in two, a first to purchase an initial quantity of services, and the second to buy a future option derivative to reserve a capacity to obtain more services in the future if the demand exceeds the paid initial portion. Derivatives of the services are used only for future reserves to demand. What is needed is a system that allows a service provider to cover risk without being forced to provide deferred services.
The use of weather derivatives is known. U.S. patent application Ser. No. 11/732,533 describes systems and modules to create customized weather derivatives. Much like option contracts, weather derivatives can be purchased by traders, but the use of derivatives is complex and difficult and often too complex to act as a useful tool to manage risk for users of services in the weather industry. What is needed is a system to manage weather risk that creates a weather derivative that minimizes financial risk to the parties while covering the service provider and the service user for any weather condition.